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ML Engineer, Cloud Platform

Prior Labs
CompanyPrior Labs
CategoryEngineering
LocationBerlin
RemoteOn-site (inferred)
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted26 Sept 2025
Last verified30 Jul 2026
SourceEmployer career page (ashby)
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Description
WHO WE ARE Foundation models transformed text and images. Structured data - the largest and most consequential data format in the world - stayed untouched. Tables run every clinical trial, every financial model, every scientific experiment, every business decision, and no one had built a foundation model that truly understood them. Until now. What LLMs did for language, we're doing for tables. The next modality shift in AI is happening, and we're hiring the team that makes it. Momentum. We pioneered tabular foundation models and are now the world-leading organization in structured-data ML. Our TabPFN v2 model was published as a Nature https://www.nature.com/articles/s41586-024-08328-6 cover story and set a new state of the art for tabular machine learning. Since release we've scaled model capabilities 20x+, passed 3.5M+ downloads and 7,500+ GitHub stars, and are seeing accelerating adoption across research and industry - from detecting lung disease with Oxford Cancer Analytics https://www.oxcan.org/news/prior-labs-and-oxford-cancer-analytics-partner-to-advance-liquid-biopsy-and-clinical-decision-making-in-lung-disease to preventing train failures with Hitachi https://siliconangle.com/2025/12/01/prior-labs-debuts-tabular-ai-foundation-model-scales-10-million-rows/ to improving clinical-trial decisions with BostonGene https://priorlabs.ai/case-studies/boston-gene. The hardest work is ahead. We're scaling tabular foundation models to millions of rows, thousands of features, real-time inference, and entirely new data modalities, while building the infrastructure to run them in production across some of the most demanding industries on earth. These are open problems no one else is working on at this level. Our team. We're a small, highly selective team https://priorlabs.ai/about of 30+ engineers, researchers, and GTM specialists, with backgrounds spanning Google, Apple, Amazon, DeepMind, Meta, Microsoft Research, G-Research, Jane Street, Goldman Sachs, and CERN. We're led by Frank Hutter https://www.linkedin.com/in/frank-hutter-9190b24b/, Noah Hollmann https://www.linkedin.com/in/noah-hollmann-668b9010b/, and Sauraj Gambhir https://www.linkedin.com/in/sauraj-g/, and advised by world-leading AI researchers including Bernhard Schölkopf and Turing Award winner Yann LeCun. We ship fast, do top-tier research, and hold each other to an extremely high bar. What's next. In 2025 we raised €9m pre-seed led by Balderton Capital, backed by leaders from Hugging Face, DeepMind, and Black Forest Labs. The next phase of growth is here, which makes this an ideal time to join. ABOUT THE ROLE You will have ownership over designing, building, and scaling the core infrastructure that brings Prior Labs' foundation models to the world. This is a unique opportunity to make fundamental architectural decisions, establish engineering best practices from the ground up, and profoundly shape the technical direction for serving state-of-the-art AI. You'll work directly with world-class AI researchers, translating cutting-edge models into reliable, scalable production systems. This role offers significant autonomy and impact, with clear paths to specialize in areas you're passionate about (like ML infrastructure or core backend systems) or grow into a technical leadership position as our team expands. You won't just be implementing features; you'll be building the backbone of our company. WHAT YOU'LL DO - Architect & Design: Design robust, scalable, and secure backend systems and production-grade APIs for serving and finetuning our foundation models. - Build & Implement: Develop high-quality, maintainable code (Python/FastAPI experience highly valued) for core backend services. - Own Infrastructure: Design, deploy, and manage core infrastructure on cloud platforms, focusing on reliability, monitoring, observability, and cost-efficiency. - Core MLOps Concepts: Understanding of the entire machine learning lifecycle (MLLC) from data
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ML Engineer, Cloud Platform — Prior Labs · Job Opportunities API